Complex event processing (CEP) is a technology in which an event is acquired from multiple event sources, a basic event is processed by using technologies such as filtering, association, and aggregation, and a complex (advanced) event is generated by means of deduction. A core of the CEP is a rule matching engine (also referred to as a CEP engine) that is used for event detection. A visual description of the CEP technology is similar to that a human body acquires basic events by using various external sensory organs, that is, different environmental phenomena; a human brain obtains a complex event by means of deduction, for example, it is going to rain, and determines an action to be taken, such as bringing the laundry.
Stream computing, that is, real-time stream computing, is to process to-be-processed data in a form of a data stream, where the data stream is a collection of a series of data records not limited in time distribution and quantity, and a data tuple is a smallest composition unit of the data stream. A most important characteristic of the real-time stream computing is a capability of responding to a computing result in real time. Value of data decreases as time elapses, and the data has to be processed as soon as possible after its presence, and preferably, data is immediately processed when the data appears. A key characteristic of the stream computing is that processing is performed once when a piece of data is generated, instead of being performed when the data is cached into a batch.
With the coming of the era of big data and large-scale application of the real-time stream computing, a traditional CEP engine gradually cannot satisfy a detection requirement of a complex event (a large data amount, a complex rule, and a high real-time requirement) in a high-speed data stream. Therefore, a complex event real-time stream processing (ESP) platform is developed based on the real-time stream computing. The ESP platform can extract, from a complex service event included in a high-speed data stream, data information that is meaningful to a user, and assist the user in performing service monitoring and decision control. Briefly, the ESP platform used to implement ESP is a stream computing platform overlaid with a CEP component.
Currently, different vendors in the industry perform update and expansion based on their original CEP engines, so as to support an ESP-related service. Different platforms use different complex event detection methods. However, affected by factors such as being limited by architecture forms of existing products of the vendors, the platforms support limited service scenarios, for example, a poor service rule customization capability and a complex customization process, which causes low performance and low usability of the complex event detection methods.